The Use of Contextual Graphs for Decision Support in Recruiting

2018;
: pp. 129 - 135
Authors: 

I. Zavushchak, Y.Burov

Department of information systems and networks, Lviv Polytechnic National University, S. Bandery Str., 12, Lviv, 79013, UKRAINE, E-mail: iryska2009@ukr.net

Taking in consideration the current context is an important requirement for knowledge based systems. The article discusses the application of context-sensitive decision support in the area of employment solutions providing. The research is based on employment area business process analysis which resulted in ontology construction. Next, the models for context representation are compared and models based on ontology and graphs are chosen for processing of contextual knowledge. Enhanced JDL model with specified context processing operations is introduced. Contextual graphs are used for representation of contextual knowledge and the operation of deepening of context is discussed. Finally, the modified analytical hierarchy method is proposed for justification of decisions about selection of practices.

  1. Quinn, J. B. The intelligent enterprise a new paradigm. The Executive, 6(4) – 1992. – pp. 48–63.
  2. Bob Lewis and Scott Lee. The Cognitive Enterprise. Meghan-Kiffer Press, Tampa, FL, USA., 2015, 212 p.
  3. Smart Machines: IBM's Watson and the Era of Cognitive Computing. Columbia Business School Publishing by John E. Kelly III, Steve Hamm https://cup.columbia.edu/book/978-0-231-16856-4/smart-machines.
  4. Mary Bazire and Patrick Brézillon. Understanding Context Before Using It. A. Dey et al. (Eds.): CONTEXT 2005, LNAI 3554, pp. 29–40, 2005. © Springer-Verlag Berlin Heidelberg 2005.
  5. Strang T, Linnhoff-Popien C. A context modeling survey. InWorkshop on advanced context modelling, reasoning and management, UbiComp 2004 Sep 7, Vol. 4, pp. 34–4).
  6. Смирнов а.в., Левашова т.в., Пашкин м.п. модели контекстно-управляемых систем поддержки принятия решений в динамических структурированных областях, 2009.
  7. Bettini, Claudio/ A survey of context modelling and reasoning techniques./ Pervasive and Mobile Computing 6.2 (2010): 161–180
  8. Ye, Juan, Lorcan Coyle, Simon Dobson, and Paddy Nixon. "Ontology-based models in pervasive computing systems". The Knowledge Engineering Review 22, no. 4 (2007): 315–347.
  9. Iryna Zavuschak. The Context of Operations as the Basis for the Construction of Ontologies of Employment Processes // Iryna Zavuschak, Yevhen Burov. /I.J. Modern Education and Computer Science, 2017, 11, 13–24 Published Online November 2017 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijmecs.2017.11.02.
  10. Steinberg, A. N. and Bowman, C. L.,. Revisions to the JDL data fusion model. // Handbook of multisensor data fusion. – CRC Press, 2008. – pp. 65–88.
  11. Cabrera O, Franch X, Marco J. A context ontology for service provisioning and consumption. InResearch Challenges in Information Science (RCIS), 2014 IEEE Eighth International Conference on 2014 May 28 (pp. 1–12).
  12. Brézillon, Patrick. Task-realization models in contextual graphs. Modeling and Using Context(2005) pp. 1–8.
  13. Brézillon, Patrick. Elaboration of the Contextual Graphs representation: From a conceptual framework to an operational software. 2017.
  14. Буров Є. Опрацювання контексту у когнітивній інформаційній системі керованій моделями Східно-Європейський журнал передових технологій № 1/7(43). – Харків:Технологічний центр. 2010 ج . – C. 40–47.